This thesis examines the marginal cost of congested travel to a variety of businesses by observing time spent in congestion and estimating excess labor costs based upon the relevant value of time. The fleets in the scoping study represented commercial deliveries of goods and services, government agencies, and transit systems. Observations on limited-access expressways within the 13-county Atlanta metropolitan region were used in the analysis. Vehicles were monitored by using a passive GPS assembly that transmitted speed and location data in real-time to an off-site location. Installation and operation during the observation period required no interaction from the driver. Over 217 hours of good freeway movement during 354 vehicle-days was recorded. Rates of delay, expressed as a unit of lost minutes per mile traveled, were calculated by taking the difference in speeds observed during congestion from an optimal free-flow speed of 45 mph and dividing that by the distance traveled per segment. The difference between the 50th and 95th percentile delay rates was used as the measure for travel unreliability. Daily average values of extra time needed per fleet vehicle to ensure on-time arrivals were derived, and the median buffer across all fleets was 1.65 hours of added time per vehicle. Weekly marginal costs per fleet vehicle were estimated by factoring in the corresponding driver wages or hourly operation costs (for transit fleets). Equivalent toll rates were calculated by multiplying the 95th percentile delay rate by the hourly costs. The equivalent toll per mile traveled was representative of an equal relationship between the marginal costs of congestion experienced and a hypothetical state of free-flow travel (under first-best rules of marginal cost pricing). The median equivalent toll rates across all fleets was $0.43 per mile for weekday mornings, $0.13 per mile for midday weekdays, $0.53 per mile for afternoon weekdays and $0.01 per mile for weekday nights and weekends.

Although most modern, highly-computerized flight decks are known to be robust to small disturbances and failures, humans still play a crucial role in advanced decision making in off-nominal situations, and accidents still occur because of poor human-automation interaction. In addition to the physical state of the environment, operators now have to extend their awareness to the state of the automated flight systems. To guarantee the accuracy of this knowledge, humans need to know the dynamics or approximate versions of the dynamics that rule the automation. The operator's situation awareness can decline because of a deficient mental model of the aircraft and an excessive workload. This work describes the creation of a computational human agent model simulating cognitive constructs such as situation awareness and mental models known to capture the symptoms of poor human-automation interaction and provide insight into more comprehensive metrics supporting the validation of automated systems in aviation.

Braess' paradox is a counter-intuitive phenomenon which can occur in congesting networks. It refers to those cases where the introduction of a new link in the network results in the total travel time on the network increasing. The dissertation starts by introducing the traffic assignment problem and the concept of equilibrium in traffic assignment. The concept of equilibrium is based on Wardrop's first principle that all travellers will attempt to minimize their own travel time regardless of the effect on others. A literature review includes details of a number of papers that have been published investigating theoretical aspects of the paradox. There is also a brief description of Game Theory and the Nash Equilibrium. It has been shown that the equilibrium assignment is an example of Nash Equilibrium. The majority of work that has been published deals with networks where the delay functions that are used to compute the travel times on the links of the network do not include explicit representation of the capacity of the links. In this dissertation a network that is similar in form to the one first presented by Braess was constructed with the difference being that the well-known BPR function was used in the delay functions. This network was used to show that a number of findings that had been presented previously using simpler functions also applied to this network. It was shown that when it occurs, Braess' paradox only occurs over a range of values at relatively low levels of congestion. Real-world networks were then investigated and it was found that similar results occurred to those found in the simpler test networks that are often used in discussions of the paradox. Two methodologies of eliminating the paradox were investigated and the results are presented. / Decision Sciences / M.Sc.

A Região Metropolitana de São Paulo (RMSP) sofre de sérios problemas de congestionamento, assim como muitas outras cidades de grande porte. Uma possível solução, proposta por pesquisadores de transportes, economia e ciências ambientais, é a implantação de um sistema de congestion charging, chamada no Brasil de pedágio urbano. Um dos objetivos do presente trabalho foi estabelecer os conceitos relacionados a este assunto e ilustrar as principais questões relacionadas à sua implantação. Espera-se que este trabalho possa auxiliar o desenvolvimento de estudos de avaliação da viabilidade e de impactos de sistemas propostos de congestion charging. Para atingir este objetivo, toca-se em diversos assuntos, como a definição de congestionamento e as formas de medi-lo, a base conceitual e teórica dos sistemas de congestion charging e seus diversos esquemas de diferenciação. São expostas também as medidas de mitigação de congestionamento que já foram implantadas na RMSP, quais foram os estudos já desenvolvidos considerando este tipo de política para a RMSP, e casos em que sistemas de congestion charging já foi implantado. Neste trabalho, desenvolveu-se também um modelo de escolha discreta a partir dos dados da Pesquisa Origem e Destino 2007 do METRÔ, onde pessoas deveriam escolher entre \"Transporte Coletivo\" e \"Transporte Público\". Este modelo foi utilizado para avaliar o potencial de impacto na divisão modal e de arrecadação de um congestion charge aplicado ao centro expandido de São Paulo. Adverte-se, porém, que os resultados obtidos são meramente ilustrativos. Mostra-se, também, que é possível avaliar a capacidade ociosa do sistema de transporte coletivo a partir dos dados disponíveis de bilhetagem e de GPS dos ônibus. Este processo é exemplificado através do cálculo de capacidade de uma única viagem de um único ônibus, dada a dificuldade de automatização deste processo para abranger toda a frota. / The São Paulo Metropolitan Region (SPMR) suffers from severe traffic congestion, as do many other large-scale urban areas around the world. A possible solution to this issue, which has been suggested by transportation, economics and environmental researchers, is the implementation of a congestion charging system. One of the objectives of this project is to establish clear concepts and shed light on the main issues regarding these systems by means of a comprehensive literary review. It is expected that this project may help the development of in-depth studies carried in order to evaluate the viability and impacts of congestion charging proposals. In order to achieve this goal, many subjects are addressed, such as the definition of congestion, how its measured, the theoretical backgrounds that support congestion charging schemes, their different degrees of differentiation, which policies were enacted in order to reduce traffic congestion in São Paulo, what considerations and studies have already been developed for Brazil and São Paulo regarding these systems and where have these systems been successfully installed. Later chapters deal with another goal of this project: estimating how a congestion charging system would affect SPMR. This was achieved through a multinomial logit model, where decision-makers choose between \"Public Transportation\" and \"Private Automobile\". The results presented at this phase are merely indicative of certain tendencies and should not be considered final. This project also attempts to show that given the available Automated Fare Collection (AFC) data and Automated Vehicle Location (AVL) data, it is possible to estimate the current public transportation system\'s unused capacity. The author shows this by calculating the capacity of one bus trip using these data, but also explains the difficulties of expanding this analysis to the whole of SPMR\'s public transportation system.

During the urbanization process, vehicles quantity increase with expansion in population. Under this situation, bus transportation system also suffers from bus delay. Bus delay could be caused by a series of factors, for instance, overload passengers, traffic jam, traffic accident and other unpredictable situations. Therefore, choosing crucial elements to efficiently evaluate bus delay is a complex problem in bus delay researches and operation management. The thesis propose an approach to evaluate and explain bus delay by two elements: traffic congestion and passengers’ waiting time. Those two elements would represent the action of external and internal factors on bus operation. This approach could be adaptive to explain the reasons for bus delays, thus to help the optimization of bus lines and give useful information for decision making of transportation company. To achieve the research aim, a GIS-T database was created by combining the GIS database and TIS database. Spatial data as well as attribute data are combined in the database to represent the crucial information for bus delay. Based on GIS-T the database, the impact of traffic congestion and passengers’ waiting time was calculated using the bus line simulation. By implementing the above steps, the main cause of bus delay was studied. A case study application of this method is narrated; focusing on optimize the bus system of Guiyang city, South China. Different methods are used to find out the problem of system and the reason for delay. Moreover, optimization suggestion is proposed according to result. Compared with other methods, the two-factor method has the advantage of locating the reason of delay for each station. The time performance is not superior to other methods. By comparing the situation of adjacent station, the proportion of traffic congestion and overload passenger in bus delay was determined. The two-factor method is applicable for other transit system in different cities which has similar structure as Guiyang. However, for cities with other structure, a feasibility should be made to select an appropriate model.

Traffic is a problem across the globe, reaching perniciously into cities and communities nearly everywhere. The United States (US) has its share of traffic problems; of the ten cities with the highest traffic delay times in 2022, four were in the US. While nearly everyone living in the US has likely experienced traffic congestion of some kind, some cities are notoriously worse than others. In New York City (NYC), traffic congestion has been a problem as far back as 1913, when Fifth Avenue was so traffic-clogged it could take 40 minutes to go 23 blocks. Today, of the 25 most congested traffic corridors in the US, three are in NYC. One of these runs through the South Bronx, an environmental justice neighborhood we highlight in this dissertation. Traffic congestion is a source of air pollution (traffic-related air pollution, or TRAP) and noise, and it can result in property damage, injuries, and fatalities from collisions with other vehicles, pedestrians, or those using other forms of transportation. Both traffic congestion and TRAP have been associated with numerous negative health outcomes. For example, TRAP is associated with respiratory, cardiovascular, neurological, and pregnancy outcomes, including asthma exacerbation, incident childhood and adult asthma, reduced lung function, atherosclerosis, hypertension, stroke, myocardial infarction, cardiovascular-related mortality, cognitive decline, neurodevelopmental outcomes, pregnancy loss, term low birth weight, and small for gestational age birth. In general across the US, communities of color and higher-poverty neighborhoods face greater exposure and health burden from traffic. Throughout this dissertation, we study traffic congestion and TRAP through two lenses: (1) environmental justice; and (2) policy. Additionally, we assess the cardiovascular health impacts of TRAP. In Chapter 1, we provide background on the problem of traffic, focusing on NYC and the South Bronx. In Chapter 2, we present a case study from the South Bronx, where a new trucking-intensive warehouse was opened in 2018. In this study, we quantified the increase in vehicles and trucks following the opening of the warehouse and estimated the resulting increases in black carbon (BC) and noise. We discuss the injustice in the methods used to assess the environmental impact of the warehouse, the warehouse’s siting in a predominantly Black and Lantinx community already overburdened with trucking-intensive industries, and the desire of the community to instead use the land for a community park. In Chapter 3, we present a study quantifying how traffic congestion in NYC changed during the COVID-19 pandemic. We assess how NY on Pause, the state’s stay-at-home order, impacted traffic congestion by comparing the magnitude of traffic decreases in environmentally burdened or systematically disadvantaged neighborhoods to the magnitude of decreases in less burdened and more advantaged neighborhoods. We discuss the implications of these results for upcoming traffic policies in NYC, such as congestion pricing. In Chapter 4, we present a study evaluating diurnal changes in TRAP in NYC during NY on Pause. We discuss the implications of these results for congestion pricing, including the potential timing of TRAP decreases. In Chapter 5, we present an epidemiologic study of TRAP and myocardial infarction (MI) in New York State, identifying hazard windows of exposure in a study period where the mean nitrogen dioxide (NO₂) concentration was substantially lower than the hourly national standard. We discuss implications for the NO₂ National Ambient Air Quality Standards (NAAQS) and suggest that the current standard may be insufficient to protect population cardiovascular health. Finally, in Chapter 6, we conclude with a discussion of recommended research directions and policy considerations.

Traffic congestion is a severe problem in urban areas and it leads to the emission of greenhouse gases and air pollution. In general, drivers lack knowledge of the location and availability of free parking spaces in urban cities. This leads to people driving around searching for parking places, and about one-third of traffic congestion in cities is due to drivers searching for an available parking lot. In recent years, various solutions to provide parking information ahead have been proposed. The vast majority of these solutions have been applied in large cities, such as Beijing and San Francisco. This thesis has been conducted in collaboration with Knowit and Dukaten to predict parking occupancy in car parks one hour ahead in the relatively small city of Linköping. To make the predictions, this study has investigated the possibility to use long short-term memory and gradient boosting regression trees, trained on historical parking data. To enhance decision making, the predictive uncertainty was estimated using the novel approach Monte Carlo dropout for the former, and quantile regression for the latter. This study reveals that both of the models can predict parking occupancy ahead of time and they are found to excel in different contexts. The inclusion of exogenous features can improve prediction quality. More specifically, we found that incorporating hour of the day improved the models’ performances, while weather features did not contribute much. As for uncertainty, the employed method Monte Carlo dropout was shown to be sensitive to parameter tuning to obtain good uncertainty estimates.

Safety and congestion are ever present and increasingly severe transportation problems in urban areas throughout the nation and world. These phenomena can have wide-ranging consequences relating to safety, the economy, and the environment. Adverse weather conditions represent another significant challenge to safety and mobility on highways. Oregon is not immune from either of these global issues. Oregon Route (OR) 217, to the southwest of the downtown Portland, is one of the worst freeways for congestion in the state and is also subject to the Pacific Northwest's frequently inclement and unpredictable climate. High crash rates, severe recurrent bottlenecks and highly unreliable travel times continuously plague the corridor, making it a major headache for the thousands of commuters using it every day. In an effort to more effectively combat both congestion and adverse weather, transportation officials all over the world have been turning to increasingly technological strategies like Active Traffic Management (ATM). This can come in many forms, but among the most common are variable speed limit (VSL) systems which use real-time data to compute and display appropriate reduced speeds during congestion and/or adverse weather. After numerous studies and deliberations, Oregon Department of Transportation (ODOT) selected Oregon Route (OR) 217 as one of the first locations in the state to be implemented with an advisory VSL system, and that system began operation in the summer of 2014. This thesis seeks to evaluate the effectiveness of this VSL system through the first eight months of its operation through an in-depth and wide-ranging "before and after" analysis. Analysis of traffic flow and safety data for OR 217 from before the VSL system was implemented made clear some of the most prevalent issues which convinced ODOT to pursue VSL. Using those issues as a basis, a framework of seven specific evaluation questions relating to both performance and safety, as well as both congestion and adverse weather, was established to guide the "before and after" comparisons. Hypotheses, and measures of effectiveness for each question were developed, and data were obtained from a diverse array of sources including freeway detectors, ODOT's incident database, and the National Oceanic and Atmospheric Administration (NOAA). The results of the various "before and after" comparisons performed as a part of this thesis indicate that conditions have changed on OR 217 in a number of ways since the VSL system was activated. Many, but not all, of the findings were consistent with the initial hypotheses and with the findings from other VSL studies in the literature. Certain locations along the corridor have seen significant declines in speed variability, supporting the common notion that VSL systems have a harmonizing effect on traffic flow. Crash rates have not decreased, but crashes have become less frequent in the immediate vicinity of VSL signs. Flow distribution between adjacent lanes has been more even since VSL implementation during midday hours and the evening peak, and travel time reliability has seen widespread improvement in three of the corridor's four primary travel lanes during those same times. The drops in flow that generally occur upstream of bottlenecks once they form have had diminished magnitudes, while the drops in flow downstream of the same bottlenecks have grown. Finally, the increase in travel times that is usually brought about by adverse weather has been smaller since VSL implementation, while the decline in travel time reliability has largely disappeared.